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- Allocca, Giancarlo, et al.
(författare)
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Validation of 'Somnivore', a Machine Learning Algorithm for Automated Scoring and Analysis of Polysomnography Data
- 2019
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Ingår i: Frontiers in Neuroscience. - : Frontiers Media S.A.. - 1662-4548 .- 1662-453X. ; 13
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Tidskriftsartikel (refereegranskat)abstract
- Manual scoring of polysomnography data is labor-intensive and time-consuming, and most existing software does not account for subjective differences and user variability. Therefore, we evaluated a supervised machine learning algorithm, Somnivore (TM), for automated wake-sleep stage classification. We designed an algorithm that extracts features from various input channels, following a brief session of manual scoring, and provides automated wake-sleep stage classification for each recording. For algorithm validation, polysomnography data was obtained from independent laboratories, and include normal, cognitively-impaired, and alcohol-treated human subjects (total n = 52), narcoleptic mice and drug-treated rats (total n = 56), and pigeons (n = 5). Training and testing sets for validation were previously scored manually by 1-2 trained sleep technologists from each laboratory. F-measure was used to assess precision and sensitivity for statistical analysis of classifier output and human scorer agreement. The algorithm gave high concordance with manual visual scoring across all human data (wake 0.91 +/- 0.01; N1 0.57 +/- 0.01; N2 0.81 +/- 0.01; N3 0.86 +/- 0.01; REM 0.87 +/- 0.01), which was comparable to manual inter-scorer agreement on all stages. Similarly, high concordance was observed across all rodent (wake 0.95 +/- 0.01; NREM 0.94 +/- 0.01; REM 0.91 +/- 0.01) and pigeon (wake 0.96 +/- 0.006; NREM 0.97 +/- 0.01; REM 0.86 +/- 0.02) data. Effects of classifier learning from single signal inputs, simple stage reclassification, automated removal of transition epochs, and training set size were also examined. In summary, we have developed a polysomnography analysis program for automated sleep-stage classification of data from diverse species. Somnivore enables flexible, accurate, and high-throughput analysis of experimental and clinical sleep studies.
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| 2. |
- Porcheret, Kate, et al.
(författare)
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Investigation of the impact of total sleep deprivation at home on the number of intrusive memories to an analogue trauma
- 2019
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Ingår i: Translational Psychiatry. - : Nature Publishing Group. - 2158-3188. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- Sleep enhances the consolidation of memory; however, this property of sleep may be detrimental in situations where memories of an event can lead to psychopathology, such as following a traumatic event. Intrusive memories of trauma are emotional memories that spring to mind involuntarily and are a core feature of post-traumatic stress disorder. Total sleep deprivation in a hospital setting on the first night after an analogue trauma (a trauma film) led to fewer intrusive memories compared to sleep as usual in one study. The current study aimed to test an extension of these findings: sleep deprivation under more naturalistic conditions-at home. Polysomnographic recordings show inconsistent sleep deprivation was achieved at home. Fewer intrusive memories were reported on day 1 after the trauma film in the sleep-deprived condition. On day 2 the opposite was found: more intrusive memories in the sleep-deprived condition. However, no significant differences were found with the removal of two participants with extreme values and no difference was found in the total number of intrusive memories reported in the week following the trauma film. Voluntary memory of the trauma film was found to be slightly impaired in the sleep deprivation condition. In conclusion, compared to our eariler findings using total sleep deprivation in a hospital setting, in the current study the use of inconsistent sleep deprivation at home does not replicate the pattern of results on reducing the number of intrusive memories. Considering the conditions under which sleep deprivation (naturalistic versus hospital) was achieved requires further examination.
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